SoroushVahidi/scidocs huggingface dataset:
Residual Highway Convolutional Neural Networks for in-loop Filtering in HEVC
(2018)

High efficiency video coding (HEVC) standard achieves half bit-rate reduction while keeping the same quality compared with AVC. However, it still cannot satisfy the demand of higher quality in real applications, especially at low bit rates. To further improve the quality of reconstructed frame while reducing the bitrates, a residual highway convolutional neural network (RHCNN) is proposed in this paper for in-loop filtering in HEVC. The RHCNN is composed of several residual highway units and convolutional layers. In the highway units, there are some paths that could allow unimpeded information across several layers. Moreover, there also exists one identity skip connection (shortcut) from the beginning to the end, which is followed by one small convolutional layer. Without conflicting with deblocking filter (DF) and sample adaptive offset (SAO) filter in HEVC, RHCNN is employed as a high-dimension filter following DF and SAO to enhance the quality of reconstructed frames. To facilitate the real application, we apply the proposed method to I frame, P frame, and B frame, respectively. For obtaining better performance, the entire quantization parameter (QP) range is divided into several QP bands, where a dedicated RHCNN is trained for each QP band. Furthermore, we adopt a progressive training scheme for the RHCNN where the QP band with lower value is used for early training and their weights are used as initial weights for QP band of higher values in a progressive manner. Experimental results demonstrate that the proposed method is able to not only raise the PSNR of reconstructed frame but also prominently reduce the bit-rate compared with HEVC reference software.
Understanding heart rate sharing: towards unpacking physiosocial space
(2012)

Advances in biosensing make it possible to include heart rate monitoring in applications and several studies have suggested that heart rate communication has potential for improving social connectedness. However, it is not known how people understand heart rate feedback, or what issues need to be taken into account when designing technologies including heart rate feedback. To explore this, we created a heart rate communication probe that was used in two qualitative in-lab studies and a two-week field trial in participants' homes. Results show that heart rate feedback is a strong connectedness cue that affects the interaction in various ways, depending on a number of interrelated factors. In particular, we found two distinct categories of effects: heart rate as information and heart rate as connection. We propose two mechanisms that could explain these observations and draw out the implications they have for future use of heartbeat communication to support social connectedness or other aspects of social interaction.
Designing Twister 2 : Efficient Programming Environment Toolkit for Big Data
(2017)

Data-driven applications are required to adapt to the everincreasing volume, velocity and veracity of data generated by a variety of sources including the Web and Internet of Things devices. At the same time, an event-driven computational paradigm is emerging as the core of modern systems designed for both database queries, data analytics and on-demand applications. MapReduce has been generalized to Map Collective and shown to be very effective in machine learning. However one often uses a dataflow computing model, which has been adopted by most major big data processing runtimes. The HPC community has also developed several asynchronous many tasks (AMT) systems according to the dataflow model. From a different point of view, the services community is moving to an increasingly event-driven model where (micro)services are composed of small functions driven by events in the form of Function as a Service(Faas) and serverless computing. Such designs allow the applications to scale quickly as well as be cost effective in cloud environments. An event-driven runtime designed for data processing consists of well-understood components such as communication, scheduling, and fault tolerance. One can make different design decisions for these components that will determine the type of applications a system can support efficiently. We find that modern systems are designed in a monolithic approach with a fixed set of choices that cannot be changed easily afterwards. Because of these design choices their functionality is limited to specific sets of applications. In this paper we study existing systems (candidate event-driven runtimes), the design choices they have made for each component, and how this affects the type of applications they can support. Further we propose a loosely coupled component-based approach for designing a big data toolkit where each component can have different implementations to support various applications. We believe such a polymorphic design would allow services and data analytics to be integrated seamlessly and expand from edge to cloud to high performance computing environments.
A comparative study between honey and povidone iodine as dressing solution for Wagner type II diabetic foot ulcers.
(2008)

Honey dressing has been used to promote wound healing for years but scanty scientific studies did not provide enough evidences to justify it benefits in the treatment of diabetic foot ulcers. We conducted a prospective study to compare the effect of honey dressing for Wagner's grade-II diabetic foot ulcers with controlled dressing group (povidone iodine followed by normal saline). Surgical debridement and appropriate antibiotics were prescribed in all patients. There were 30 patients age between 31 to 65-years-old (mean of 52.1 years). The mean healing time in the standard dressing group was 15.4 days (range 9-36 days) compared to 14.4 days (range 7-26 days) in the honey group (p < 0.005). In conclusion, ulcer healing was not significantly different in both study groups. Honey dressing is a safe alternative dressing for Wagner grade-II diabetic foot ulcers.
A Tutorial on Support Vector Machines for Pattern Recognition
(1998)

The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail. We describe a mechanical analogy, and discuss when SVM solutions are unique and when they are global. We describe how support vector training can be practically implemented, and discuss in detail the kernel mapping technique which is used to construct SVM solutions which are nonlinear in the data. We show how Support Vector machines can have very large (even infinite) VC dimension by computing the VC dimension for homogeneous polynomial and Gaussian radial basis function kernels. While very high VC dimension would normally bode ill for generalization performance, and while at present there exists no theory which shows that good generalization performance is guaranteed for SVMs, there are several arguments which support the observed high accuracy of SVMs, which we review. Results of some experiments which were inspired by these arguments are also presented. We give numerous examples and proofs of most of the key theorems. There is new material, and I hope that the reader will find that even old material is cast in a fresh light.
Characterization of the Impact of Hardware Islands on OLTP
(2015)

Modern hardware is abundantly parallel and increasingly heterogeneous. The numerous processing cores have non-uniform access latencies to the main memory and processor caches, which causes variability in the communication costs. Unfortunately, database systems mostly assume that all processing cores are the same and that microarchitecture differences are not significant enough to appear in critical database execution paths. As we demonstrate in this paper, however, non-uniform core topology does appear in the critical path and conventional database architectures achieve suboptimal and even worse, unpredictable performance. We perform a detailed performance analysis of OLTP deployments in servers with multiple cores per CPU (multicore) and multiple CPUs per server (multisocket). We compare different database deployment strategies where we vary the number and size of independent database instances running on a single server, from a single shared-everything instance to fine-grained shared-nothing configurations. We quantify the impact of non-uniform hardware on various deployments by (a) examining how efficiently each deployment uses the available hardware resources and (b) measuring the impact of distributed transactions and skewed requests on different workloads. We show that no strategy is optimal for all cases and that the best choice depends on the combination of hardware topology and workload characteristics. Finally, we argue that transaction processing systems must be aware of the hardware topology in order to achieve predictably high performance.
An evaluation study of BigData frameworks for graph processing
(2013)

When Google first introduced the Map/Reduce paradigm in 2004, no comparable system had been available to the general public. The situation has changed since then. The Map/Reduce paradigm has become increasingly popular and there is no shortage of Map/Reduce implementations in today's computing world. The predominant solution is currently Apache Hadoop, started by Yahoo. Besides employing custom Map/Reduce installations, customers of cloud services can now exploit ready-made made installations (e.g. the Elastic Map/Reduce System). In the mean time, other, second generation frameworks have started to appear. They either fine tune the Map/Reduce model for specific scenarios, or change the paradigm altogether, such as Google's Pregel. In this paper, we present a comparison between these second generation frameworks and the current de-facto standard Hadoop, by focusing on a specific scenario: large-scale graph analysis. We analyze the different means of fine-tuning those systems by exploiting their unique features. We base our analysis on the k-core decomposition problem, whose goal is to compute the centrality of each node in a given graph; we tested our implementation in a cluster of Amazon EC2 nodes with realistic datasets made publicly available by the SNAP project.
Optimistic Optimization of a Deterministic Function without the Knowledge of its Smoothness
(2011)

We consider a global optimization problem of a deterministic function f in a semimetric space, given a finite budget of n evaluations. The function f is assumed to be locally smooth (around one of its global maxima) with respect to a semi-metric l. We describe two algorithms based on optimistic exploration that use a hierarchical partitioning of the space at all scales. A first contribution is an algorithm, DOO, that requires the knowledge of l. We report a finite-sample performance bound in terms of a measure of the quantity of near-optimal states. We then define a second algorithm, SOO, which does not require the knowledge of the semimetric l under which f is smooth, and whose performance is almost as good as DOO optimally-fitted.
Classification ability of single hidden layer feedforward neural networks
(2000)

Multilayer perceptrons with hard-limiting (signum) activation functions can form complex decision regions. It is well known that a three-layer perceptron (two hidden layers) can form arbitrary disjoint decision regions and a two-layer perceptron (one hidden layer) can form single convex decision regions. This paper further proves that single hidden layer feedforward neural networks (SLFN's) with any continuous bounded nonconstant activation function or any arbitrary bounded (continuous or not continuous) activation function which has unequal limits at infinities (not just perceptrons) can form disjoint decision regions with arbitrary shapes in multidimensional cases. SLFN's with some unbounded activation function can also form disjoint decision regions with arbitrary shapes.
Reactions to discrimination, stigmatization, ostracism, and other forms of interpersonal rejection: a multimotive model.
(2009)

This article describes a new model that provides a framework for understanding people's reactions to threats to social acceptance and belonging as they occur in the context of diverse phenomena such as rejection, discrimination, ostracism, betrayal, and stigmatization. People's immediate reactions are quite similar across different forms of rejection in terms of negative affect and lowered self-esteem. However, following these immediate responses, people's reactions are influenced by construals of the rejection experience that predict 3 distinct motives for prosocial, antisocial, and socially avoidant behavioral responses. The authors describe the relational, contextual, and dispositional factors that affect which motives determine people's reactions to a rejection experience and the ways in which these 3 motives may work at cross-purposes. The multimotive model accounts for the myriad ways in which responses to rejection unfold over time and offers a basis for the next generation of research on interpersonal rejection.
An Energy-Efficient , Wireless Top-of-Rack to Top-of-Rack Datacenter Network using 60 GHz Links
(2017)

Datacenters have become the digital backbone of the modern society and consume enormous amounts of power. Significant portion of the power consumption is due to the power hungry switching fabric necessary for communication in the datacenter. Additionally, the complex cabling in traditional datacenters pose design and maintenance challenges and increase the energy cost of the cooling infrastructure by obstructing the flow of chilled air. Recent research on wireless datacenters have proposed interconnecting rows of racks at the top-of-rack (ToR) level via wireless links to eliminate the need for complex network of power hungry routers and cables. Links are established using either highly directional phased array antennas or narrow-beam horned antennas between those ToR entities. ToR-to-ToR wireless links have also been used to augment existing wired networks, improving overall performance characteristics. All these wireless approaches advocate the use of 60GHz line-of-sight (LoS) communication paths between antennas for the establishment of reliable wireless channels. In this work, we explore the feasibility of a ToR-to-ToR wireless network for a small to medium-scale datacenter from the perspective of system-level performance. We evaluate a ToR-to-ToR wireless datacenter network (DCN) for network-level data rate and overall power consumption and compare it to a traditional fat-tree based DCN. We find that the ToR-to-ToR wireless DCN can sustain similar data rates for typical query based applications and consume less power compared to that of traditional datacenters. KeywordsWireless datacenter; Energy Efficiency; 60GHz; IEEE 802.11ad; Top-of-Rack;
2D diffuse optical imaging using clustered sparsity
(2014)

Diffuse optical imaging (DOI) is a non-invasive technique which measures hemodynamic changes in the tissue with near infrared light, and has been increasingly used to study brain functions. Due to the nature of light propagation in the tissue, the reconstruction problem is severely ill-posed. Sparsity-regularization has achieved promising results in recent works for linearized DOI problem. In this paper, we exploit more prior information to improve DOI besides sparsity. Based on the functional specialization of the brain, the in vivo absorption changes caused by specific brain function can be clustered in certain region(s) and not randomly distributed. Thus, a new algorithm is proposed to utilize this prior in reconstruction. Results of numerical simulations and phantom experiments have demonstrated the superiority of the proposed method over the state-of-the-art.
The ethics of representation and action in virtual reality
(2004)

This essay addresses ethical aspects of the design and use of virtual reality (VR) systems, focusing on the behavioral options made available in such systems and the manner in which reality is represented or simulated in them. An assessment is made of the morality of ‘immoral’ behavior in virtual reality, and of the virtual modeling of such behavior. Thereafter, the ethical aspects of misrepresentation and biased representation in VR applications are discussed.
Caricature synthesis with feature deviation matching under example-based framework
(2018)

Example-based caricature synthesis techniques have been attracting large attentions for being able to generate attractive caricatures of various styles. This paper proposes a new example-based caricature synthesis system using a feature deviation matching method as a cross-modal distance metric. It employs the deviation values from average features across different feature spaces rather than the values of features themselves to search for similar components from caricature examples directly. Compared with traditional example-based systems, the proposed system can generate various styles of caricatures without requiring paired photograph–caricature example databases. The newly designed features can effectively capture visual characteristics of the hairstyles and facial components in input portrait images. In addition, this system can control the exaggeration of individual facial components and provide several similarity-based candidates to satisfy users’ different preferences. Experiments are conducted to prove the above ideas.
Lessons from applying the systematic literature review process within the software engineering domain
(2007)

A consequence of the growing number of empirical studies in software engineering is the need to adopt systematic approaches to assessing and aggregating research outcomes in order to provide a balanced and objective summary of research evidence for a particular topic. The paper reports experiences with applying one such approach, the practice of systematic literature review, to the published studies relevant to topics within the software engineering domain. The systematic literature review process is summarised, a number of reviews being undertaken by the authors and others are described and some lessons about the applicability of this practice to software engineering are extracted. The basic systematic literature review process seems appropriate to software engineering and the preparation and validation of a review protocol in advance of a review activity is especially valuable. The paper highlights areas where some adaptation of the process to accommodate the domain-specific characteristics of software engineering is needed as well as areas where improvements to current software engineering infrastructure and practices would enhance its applicability. In particular, infrastructure support provided by software engineering indexing databases is inadequate. Also, the quality of abstracts is poor; it is usually not possible to judge the relevance of a study from a review of the abstract alone. 2006 Elsevier Inc. All rights reserved.
SLR-Tool - A Tool for Performing Systematic Literature Reviews
(2010)

Systematic literature reviews (SLRs) have been gaining a significant amount of attention from Software Engineering researchers since 2004. SLRs are considered to be a new research methodology in Software Engineering, which allow evidence to be gathered with regard to the usefulness or effectiveness of the technology proposed in Software Engineering for the development and maintenance of software products. This is demonstrated by the growing number of publications related to SLRs that have appeared in recent years. While some tools exist that can support some or all of the activities of the SLR processes defined in (Kitchenham & Charters, 2007), these are not free. The objective of this paper is to present the SLR-Tool, which is a free tool and is available on the following website: http://alarcosj.esi.uclm.es/SLRTool/, to be used by researchers from any discipline, and not only Software Engineering. SLR-Tool not only supports the process of performing SLRs proposed in (Kitchenham & Charters, 2007), but also provides additional functionalities such as: refining searches within the documents by applying text mining techniques; defining a classification schema in order to facilitate data synthesis; exporting the results obtained to the format of tables and charts; and exporting the references from the primary studies to the formats used in bibliographic packages such as EndNote, BibTeX or Ris. This tool has, to date, been used by members of the Alarcos Research Group and PhD students, and their perception of it is that it is both highly necessary and useful. Our purpose now is to circulate the use of SLR-Tool throughout the entire research community in order to obtain feedback from other users.
Evidence-based software engineering
(2004)

Objective: Our objective is to describe how softwareengineering might benefit from an evidence-basedapproach and to identify the potential difficultiesassociated with the approach.Method: We compared the organisation and technicalinfrastructure supporting evidence-based medicine (EBM)with the situation in software engineering. We consideredthe impact that factors peculiar to software engineering(i.e. the skill factor and the lifecycle factor) would haveon our ability to practice evidence-based softwareengineering (EBSE).Results: EBSE promises a number of benefits byencouraging integration of research results with a view tosupporting the needs of many different stakeholdergroups. However, we do not currently have theinfrastructure needed for widespread adoption of EBSE.The skill factor means software engineering experimentsare vulnerable to subject and experimenter bias. Thelifecycle factor means it is difficult to determine howtechnologies will behave once deployed.Conclusions: Software engineering would benefit fromadopting what it can of the evidence approach providedthat it deals with the specific problems that arise from thenature of software engineering.
Factors Influencing the Usage of Websites: The Case of a Generic Portal in the Netherlands
(2001)

In this paper, we empirically investigate an extension of the Technology Acceptance Model (TAM, Davis, 1989) to explain the individual acceptance and usage of websites. Conceptually, we examine perceived ease-of-use, usefulness, enjoyment, and their impact on attitude towards using, intention to use and actual use. The paper also introduces a new construct, “perceived visual attractiveness” of the website and suggest that it influences usefulness, enjoyment, and ease-of-use. For our empirical research we partnered with a Dutch generic portal site with over 300 000 subscribers at the time the research was conducted. The websurvey resulted in sample size of 825 respondents. The results confirmed all of the 12 hypotheses formulated. Three findings are worth mentioning in particular: (1) intention is most dominantly influenced by attitude (β = 0.51), (2) ease-of-use, enjoyment, and usefulness contribute equally to attitude towards using (β = 0.23, 0.23, and 0.17 respectively) and (3) visual attractiveness contributes remarkably well to both ease-of-use, enjoyment, and usefulness (β = 0.41, 0.35, and 0.21). Although this is not the first research to apply TAM to an internet context, we claim three major contributions: (1) a single website as the unit of analysis, (2) the introduction of visual attractiveness, and (3) the use of “real” website visitors rather than student samples. Promising future research lies in the conceptual connection between actual website features and website use, a connection for which the TAM framework provides a meaningful bridge. Factors Influencing the Usage of Websites: The Case of a Generic Portal in the Netherlands